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Future-aware geometry tokens enable autonomous vehicles to make safer and more efficient driving decisions, outperforming existing models.
Teaching VLMs to "look back" and "look ahead" with lightweight spatial reasoning tasks unlocks surprisingly strong navigation performance.
Latent reasoning can beat explicit Chain-of-Thought – but only if you force it to learn causal dynamics via a visual world model, not just language.
Imagine controlling a robotic dog with simple voice commands, instantly switching between complex skills like obstacle avoidance and object manipulation.
Ditch language descriptions: this new driving model leverages dense 3D geometry for superior autonomous driving performance and cross-camera generalization.
